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Three-dimensional point cloud semantic segmentation for cultural heritage: a comprehensive review
S Yang, M Hou, S Li - Remote Sensing, 2023 - mdpi.com
In the cultural heritage field, point clouds, as important raw data of geomatics, are not only
three-dimensional (3D) spatial presentations of 3D objects but they also have the potential …
three-dimensional (3D) spatial presentations of 3D objects but they also have the potential …
Registration of large-scale terrestrial laser scanner point clouds: A review and benchmark
This study had two main aims:(1) to provide a comprehensive review of terrestrial laser
scanner (TLS) point cloud registration methods and a better understanding of their strengths …
scanner (TLS) point cloud registration methods and a better understanding of their strengths …
Rpm-net: Robust point matching using learned features
Abstract Iterative Closest Point (ICP) solves the rigid point cloud registration problem
iteratively in two steps:(1) make hard assignments of spatially closest point …
iteratively in two steps:(1) make hard assignments of spatially closest point …
RoReg: Pairwise point cloud registration with oriented descriptors and local rotations
We present RoReg, a novel point cloud registration framework that fully exploits oriented
descriptors and estimated local rotations in the whole registration pipeline. Previous …
descriptors and estimated local rotations in the whole registration pipeline. Previous …
Evolutionary multiform optimization with two-stage bidirectional knowledge transfer strategy for point cloud registration
Point cloud registration is an important task in computer vision, where the goal is to estimate
a transformation to align a pair of point clouds. Most of the existing registration methods face …
a transformation to align a pair of point clouds. Most of the existing registration methods face …
You only hypothesize once: Point cloud registration with rotation-equivariant descriptors
In this paper, we propose a novel local descriptor-based framework, called You Only
Hypothesize Once (YOHO), for the registration of two unaligned point clouds. In contrast to …
Hypothesize Once (YOHO), for the registration of two unaligned point clouds. In contrast to …
WHU-helmet: A helmet-based multisensor SLAM dataset for the evaluation of real-time 3-D map** in large-scale GNSS-denied environments
Real-time 3-D map** of large-scale global navigation satellite system (GNSS)-denied
environments plays an important role in forest inventory management, disaster emergency …
environments plays an important role in forest inventory management, disaster emergency …
Evolutionary multitasking descriptor optimization for point cloud registration
Point cloud registration is an important task for other point cloud tasks. Feature-based
methods are widely adopted for their speed and efficiency in point cloud registration. The …
methods are widely adopted for their speed and efficiency in point cloud registration. The …
Point cloud registration based on one-point ransac and scale-annealing biweight estimation
Point cloud registration (PCR) is an important task in photogrammetry and remote sensing,
whose goal is to seek a seven-parameter similarity transformation to register a pair of point …
whose goal is to seek a seven-parameter similarity transformation to register a pair of point …
Quatro++: Robust global registration exploiting ground segmentation for loop closing in LiDAR SLAM
H Lim, B Kim, D Kim, E Mason Lee… - … International Journal of …, 2024 - journals.sagepub.com
Global registration is a fundamental task that estimates the relative pose between two
viewpoints of 3D point clouds. However, there are two issues that degrade the performance …
viewpoints of 3D point clouds. However, there are two issues that degrade the performance …